Electromagnetic Biology and Medicine最新文献

Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues. Individuals frequently struggle with sensory abnormalities, motor deficiencies affecting coordination, and cognitive impairments affecting memory and focus. In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. First, input images are taken from the brain tumour Dataset. To execute this, the input image is pre-processed using Multivariate Fast Iterative Filtering (MFIF) and it reduces the occurrence of over-fitting from the collected dataset; then feature extraction using Self-Supervised Nonlinear Transform (SSNT) to extract essential features like model, shape, and intensity. Then, the proposed PACDNN-COA-BTI-MRI is implemented in Matlab and the performance metrics Recall, Accuracy, F1-Score, Precision Specificity and ROC are analysed. Performance of the PACDNN-COA-BTI-MRI approach attains 16.7%, 20.6% and 30.5% higher accuracy; 19.9%, 22.2% and 30.1% higher recall and 16.7%, 21.9% and 30.8% higher precision when analysed through existing techniques brain tumor identification using MRI-Based Deep Learning Approach for Efficient Classification of Brain Tumor (MRI-DLA-ECBT), MRI-Based Brain Tumor Detection using Convolutional Deep Learning Methods and Chosen Machine Learning Techniques (MRI-BTD-CDMLT) and MRI-Based Brain Tumor Image Detection using CNN-Based Deep Learning Method (MRI-BTID-CNN) methods, respectively.

Due to the increase in data rate in mobile communication and the widespread use of mobile internet, electromagnetic communication systems are increasing daily. This situation causes increases in the use of more mobile communication devices and environmental non-ionizing Electromagnetic Field (EMF) levels. The rise of bee deaths and colony losses in beekeeping parallel to the increase of the EMF sources cause the concept of "electromagnetic pollution" to be considered among the reasons. Therefore, studying the effects of non-ionizing Electromagnetic Radiation (EMR) on the health of living things is one of the most significant issues today. The bees determine their direction with the Earth's magnetic field. Electromagnetic signals emitted by GSM base stations, etc. may affect the direction-finding capabilities of honey bees and constitute a stress factor. In this study, the aim was to determine the effect of EMF on honey bees and honey yield. Honey bee colonies were used, obtained from the same farm in the Trabzon region, and equalized in all respects. Moreover, these colonies were divided into five groups randomly as experiments and control groups. The experiment hives were exposed to the EMF in the frequency band of the Wi-Fi signals (2.4 GHz) and the high-voltage line (50 hz). The control hives are located far away from the EMR sources. The study was repeated in the second year to confirm the results. During the investigation, some physiological and behavioural effects of bees, such as aggressiveness, brood area, etc. were determined based on EMR exposure.

This study examined the impact of 6 GHz (0.054 W/kg SAR) Radiofrequency-Electromagnetic Field (RF-EMF) on prenatal bone development. In this study, 20 female and 20 male Wistar Albino rats divided into four groups. The Control group received no treatment, while in Group-I, only male rats were exposed to RF-EMF, female rats had no exposure. Group-II, both male and female rats received RF-EMF treatment. While in Group-III, only female rats were exposed to RF-EMF, male rats had no exposure. The exposure lasted 4 hours per day for 6 weeks. The rats were then allowed to mate within the group. After pregnancy, pregnant rats (Group-II and III) were exposed 4 hours per day for 18 days. On the 18th day of gestation, fetuses were removed and their weight and various lengths were measured. The skeletal system development of fetuses was examined with double skeletal staining method and assessed ossification in the extremities. In the study, fetal weights, head-tail length, occipital-frontal and parietal-parietal lengths significantly increased in all exposure groups when compared to the control group (p < 0.001). Although occipital-frontal length was smallest in Group-I, Group-II and Group-III were more higher than the control group (p < 0.001). The bones of the anterior and posterior extremities showed significant increases in length, ossification zone length, and ossification percentage in all experimental groups compared to the control group (p < 0.001). Our study showed that rats exposed to 6 GHz (0.054 W/kg) RF-EMF during the prenatal period had significant increases in bone development.

Objective: The aim of this study was to systematically review the preclinical studies that have applied the static magnetic field to wound healing.

Methods: The search strategy was performed in databases: PubMed, Embase, Scopus, Web of Science, LILACS, CINAHL and Cochrane Database, and in gray literature. The inclusion criteria were: Pre-clinical studies, either with a separate control/sham parallel-group or cross-over design in rodents that used magnets to treat skin injuries anywhere on the body. The risk of bias tool was the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE).

Results: Eight randomized clinical trials were included. Wound rate area DM experimental vs DM sham [MD = 2.19, 95% CI, (-0.61, 4.99), I² 25%, p = 0.13] and wound rate area - DM experimental vs non-DM control [MD = 3.33, 95% CI, (-1.86, 8.55), I² 63%, p = 0.21] were not statistically significant. A significant improvement in gross healing time in the experimental group DM compared to the DM sham [MD = -4.48, IC 95%, (-7.88, -1.07), I² 38%, p = 0.010]. The same way tensile strength - DM and non DM subgroup analysis showed improved tensile strength in both the non-diabetic and diabetic experiment groups [SMD = 1.36, 95% CI, (0.60, 2.12), I² 0%, p = 0.0005].

Conclusions: Although not statistically significant, the static magnetic field had a positive effect on wound healing in rodents compared to the sham or control group. There was a significant improvement in the assessment of healing time and skin tensile strength.

The current investigation explores tri-hybrid mediated blood flow through a ciliary annular model, designed to emulate an endoscopic environment. The human circulatory system, driven by the metachronal ciliary waves, is examined in this study to understand how ternary nanoparticles influence wave-like flow dynamics in the presence of interfacial nanolayers. We also analyze the effect of an induced magnetic field on Ag-Cu-$A{l}_2{O}_3$/blood flow within the annulus, focusing on thermal radiation, heat sources, buoyancy forces and ciliary motion. The Casson fluid model characterizes the non-Newtonian viscous properties of the biofluid. To describe the steady fluid flow mathematically, we use coupled partial differential equations and apply the homotopy perturbation method to derive rapidly convergent series solutions for the non-linear flow equations. The obtained hemodynamic consequences are graphically represented with the variations of emerging parameters. These are significantly influenced by the rheological factors of the nanofluid flow, improving flow velocity with changes in shear viscosity, while a decrease in flow is observed for intensified Lorentz forces. Ciliary motion accelerates the expansion of the induced magnetic field on nanolayers, while a higher Magnetic Reynolds number decreases the current density distribution. Increased radiative heat generation lowers the temperature, indicating that thermal radiation enhances heat transfer and improves cooling efficiency. In contrast, an increased ciliary length along the wall raises the temperature due to wave-like motion, which strengthens the thermal boundary layer in the fluid flow. Additionally, a higher nanoparticle concentration increases wall shear stress due to frictional forces, while enhanced magnetic forces decrease the shear stress along the ciliary wall. Furthermore, a higher Strommer's number may regulate the formation of blood boluses in the wavy flow. The key findings play an important role in the development of analytical benchmarks to validate computational methods, ensuring accuracy in clinical research tools and supporting reliable medical applications.

The advantages of Magnetic Coupling Resonant Wireless Power Transfer (MCR-WPT) technology include long transmission distance, high efficiency, and high power. Therefore, it shows great potential in the field of smart home. This study aims to explore the specific impacts on the cognitive functions and neuronal excitation of mice exposed to the electromagnetic fields (EMF) emitted by the MCR-WPT platform, thereby providing biological solid experimental evidence for developing Wireless Power Transfer (WPT) technology. The research employed a frequency of 90 kHz, which is suitable for wireless charging of household appliances. Mice were exposed to EMF emitted by the WPT biosafety experimental platform for various durations. And they were divided into four groups (control group, 2-week exposure group, 4-week exposure group, and 8-week exposure group). Upon completion of the exposure period, the study employed the Novel Object Recognition (NOR) test to evaluate the learning and memory capabilities of the animals. Following this, whole-cell patch-clamp experiments were conducted to record the action potentials (AP) and potassium currents. It was revealed by our observations that, in comparison to mice without electromagnetic exposure, long-term exposure to WPT-emitted EMF resulted in accelerated release of action potentials, inhibited the activation of Voltage-Gated Potassium Channels (VGKCs) current, accelerated the deactivation of K⁺ channel current, and thus significantly improved the excitability of neurons in the dentate gyrus (DG) of the hippocampus of mice, but did not significantly affect cognitive function.

Biomagnetic fluid dynamics (BFD) is an emerging and promising field within fluid mechanics, focusing on the dynamics of bio-fluids like blood in the presence of magnetic fields. This research is crucial in the medical arena for applications such as medication delivery, diagnostic and therapeutic procedures, prevention of excessive bleeding, and treatment of malignant tumors using magnetic particles. This study delves into the intricacies of blood flow induced by cilia, carrying trihybrid nanoparticles (gold, copper, and titania), within a catheterized arterial annulus under a robust magnetic field. The model incorporates factors like Hall and ion-slip currents (electromagnetic effects on charged particles), metachronal propulsion (movement of cilia for propulsion), viscous dissipation, and entropy. The physical equations in the model are transformed from the laboratory frame to a wave frame and then simplified using conditions like low Reynolds number and long wavelength. Optimal series solutions are obtained through the homotopy perturbation method (HPM). The research explores how various physical parameters shape the bloodstream's features, presenting and analyzing these visually. A notable finding is that an intensification in Hall and ion-slip parameters results in higher blood velocity within the catheterized annulus. Blood cooling is observed with a higher loading of suspended nanoparticles. Entropy generation increases with growing values of Hall and ion-slip parameters, while the reverse trend is noted for the Bejan number. The wall shearing stress (WSS) reduces by 2.84% for 1% increase in Hall parameter. The study also provides a brief overview of how blood boluses (or clumps of blood) are structured under the influence of operating parameters. The modified hybrid nano-blood (MHNB) forms smaller and fewer boluses compared to pure blood (PB). Additionally, longer cilia length results in enhanced trapping of boluses due to stronger recovery motions of the cilia. This research holds potential benefits for practitioners and researchers in diagnosing and assessing conditions such as coronary artery disease, valvular heart disease, and congenital heart abnormalities, as well as for understanding traumatic brain injury and neurological surgeries.

Anxiety is an adaptive condition characterized by heightened uneasiness, which in the long term can cause complications such as reducing the quality of life and problems related to the mental and physical health. Concerns have been raised regarding the potential dangers of extremely low frequency electromagnetic fields (ELF-EMF) ranging from 3 to 3000 Hz, which are omnipresent in our daily lives and there have been studies about the anxiogenic effects of these fields. Studies conducted in this specific area has revealed that ELF-EMF can have an impact on various brain regions, such as the hippocampus. In conclusion, studies have shown that ELF-EMF can interfere with hippocampus-prefrontal cortex pathway, inducing anxiety behavior. Also, ELF-EMF may initiate anxiety behavior by generating oxidative stress in hypothalamus and hippocampus. Moreover, ELF-EMF may induce anxiety behavior by reducing hippocampus neuroplasticity and increasing the NMDA2_A receptor expression in the hippocampus. Furthermore, supplementation with antioxidants could serve as an effective protective measure against the adverse effects of FLF-FMF in relation to anxiety behavior.

The electromagnetic waves of 2.45 GHz microwave frequency have become abundant in environments worldwide. This study assessed the short-term impact of low-intensity 2.45 GHz exposure on young Arabidopsis thaliana plants. The plants underwent a 48-hour exposure to continuous wave 2.45 GHz microwaves at a power density of 1.0 ± 0.1 W m^-2. Experiments were conducted inside anechoic chambers. After the microwave exposure samples were subjected to morphological, genotoxicity, pigmentation, and physiochemical analysis. Microwave exposure elevated the levels of photosynthetic pigments, oxidative stress, guaiacol peroxidase activity, and ascorbic peroxidase activity in plants. Conversely, catalase activity decreased. Photosystem efficiency remained unchanged, while non-photochemical quenching increased. Leaf morphological parameters exhibited no significant alterations during this brief exposure period. Notably, despite shifts in physiological parameters and pigmentations, genomic template stability remained unaffected. The findings suggest that the non-thermal effects of microwave exposure influence the photosystem and plant physiology. Research confirmed the existence of non-thermal effects of microwave exposure; however, these effects are within tolerable limits for Arabidopsis thaliana plants.

Human being's biological processes and psychological activities are jointly connected to the brain. So, the examination of human activity is more significant for the well-being of humans. There are various models for brain activity detection considering neuroimaging for attaining decreased time requirement, increased control commands, and enhanced accuracy. Motor Imagery (MI)-based Brain-Computer Interface (BCI) systems create a way in which the brain can interact with the environment by processing Electroencephalogram (EEG) signals. Human Activity Recognition (HAR) deals with identifying the physiological activities of human beings based on sensory signals. This survey reviews the different methods available for HAR based on MI-EEG signals. A total of 50 research articles based on HAR from EEG signals are considered in this survey. This survey discusses the challenges faced by various techniques for HAR. Moreover, the papers are assessed considering various parameters, techniques, publication year, performance metrics, utilized tools, employed databases, etc. There were many techniques developed to solve the problem of HAR and they are classified as Machine Learning (ML) and Deep Learning (DL)models. At last, the research gaps and limitations of the techniques were discussed that contribute to developing an effective HAR.